design of a mathematical model for logistic network in a multi-stage multi-product supply chain network and developing a metaheuristic algorithm

logistic network design is one of the most important strategic decisions in supply chain management that has recently attracted the attention of many researchers. transportation network design is then one of the most important fields of logistic network. this study is concerned with designing a multi-stage and multi-product logistic network. at first, a mixed integer nonlinear programming model (minlp) is formulated that minimizes transportation and holding costs. then, a hybrid priority-based genetic algorithm (pb-ga) andsimulated annealing algorithm (sa) is developed in two phases to find the optimal solution. the solution is represented by a matrix and a vector. response surface methodology (rsm) is also used to adjust the significant parameters of the algorithm. finally, several test problems are generated which show that the proposed metaheuristic algorithm can find good solutions in reasonable time spans.